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Staphylococcus aureus: characterization of resistance and virulence factors in strains isolated from mastitic bovine milk and the use of comparative genomics and phylogenetic tests in search of disease markers


Bovine mastitis is one of the most costly diseases of dairy cattle and can lead to risks to public health due to milk contamination. S. aureus is considered the main etiological agent and its epidemiology is associated with its phenotypic diversity and if multiple genomes could be analyzed, it would be possible to infer factors that could predict pathogenic and resistant phenotypes. With this, the present work aims to characterize isolates of S. aureus in relation to several factors of virulence and resistance and also to perform a comparative genomic and phylogenetic analysis to investigate the relationship between S. aureus involved in bovine and human mastitis and the relationship between the genetic profile of these strains and mastitis. For this, strains of S. aureus from samples of mastitic milk isolated from animals of Concórdia - Santa Catarina will be used. These strains will be submitted to PCR to detect virulence genes related to toxic shock, exfoliative toxins, coagulase toxin and enterotoxins. Subsequently, genes for resistance to aminoglycoside, beta-lactam, tetracycline and erythromycin antimicrobials will be investigated. Then, Pulsed Field Gel Electrophoresis (PFGE) will be performed to investigate the genetic similarity of these strains. Furthermore, strains of S. aureus obtained from samples isolated from cattle and humans available at the "National Center for Biotechnology Information" (NCBI) will be evaluated for the presence of virulence and resistance genes already described, as well as the phylogenetic correlation of these genes will be evaluated. obtained through phylogenic assays. The alignment of gene sequences and, subsequently, phylogenetic trees will be generated with the aid of MAFFT v7. Based on the presence and absence of genes, the hierarchical cluster analysis will be performed using PAST v4.03 software, correlation between presence / absence of genes, analysis of incorporation of stochastic neighbors with T distribution (TSNE) and profile heat map of genes will be carried out by the data science packages Numpy and Matplotlib and also by the software R. The obtained results will be important to understand the prevalence of S. aureus in the productive system and also by the possibility of finding genetic patterns that are markers of mastitis, disease caused by this agent. (AU)

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